In all cellular systems, a mobile station needs to constantly receive neighbor list assignments for handoffs between one base station and another base station as the mobile station moves out of the range of one cell and into the range of a new cell. However, there is an amount of uncertainty as to which cell the mobile station will move into and thus which base station will best be able to serve the mobile station. Neighbor lists help in the handoff by providing the mobile station with candidate cells. That is, those cells that could become the serving cell for the mobile station.
Today's neighbor lists are determined based on a variety of inputs ranging from path-loss predictions to field measurements, and may also include intuition on the part of the systems or field engineer. From these inputs, a list of possible neighbors of any given cell is selected and saved for any mobile that is served by that cell.
However, many of the current cellular systems have shortcomings in generating and assigning an appropriate neighbor list to the mobile station. Consequently, the mobile station may not receive the most optimal neighbor list and hence the correct neighbor does not become a handover candidate at the appropriate time. This can result in poor signal quality if the mobile station is connected to the wrong base station due to the inaccuracies in the neighbor list. These problems can also cause too many dropped calls to occur.
Moreover, in most cases the neighbor list selection tends to include all possible situations that any given mobile unit may experience which makes the neighbor list assignments large. This is especially true with respect to dense call systems or cell sectorization where a cell is divided into six sectors with each sector having multiple sectors of multiple cells as its neighbors.
A further problem that is encountered is when the neighbor list is based on the serving cell(s) of the mobile station's current call connection (i.e. a cell-centric assignment), and thus the list contains neighbors that have little relevance to the current location of the mobile. Another issue is that the time needed to scan the neighbors is detrimentally slow relative to a rapidly changing signal because the neighbor lists are often too large. Lastly, there is a limit on the number of neighbors a mobile can be told to scan and when the limit is reached, potentially desirable neighbors do not get scanned. In effect, the neighbor list is artificially truncated.
FIG. 1 helps to illustrate some of the above-stated problems. A mobile served by cell I may need to hand over to one set of neighbors as it moves through region A, such as cells II and III. The mobile station may need to hand over to a second set of neighbors as it moves through region B such as cells V and VI, and it may need to hand over to yet a third set of neighbors as it moves through region C such as cells VI and VII. Accounting for all of these possibilities creates a sizable neighbor list, and one that is less than optimal from the perspective of the time needed to scan all of them. Many of these neighbors do not need to be scanned. In fact, scanning them can lead to measurement falsing on reused frequencies or pilot offsets. Furthermore, a cell-centric method of generating a neighbor list would include cells II-VII, but if the mobile station is in region C, cells II-V have little relevance to the location of the mobile station.
Furthermore, if there was an obstacle 13 such as vehicular traffic, seasonal vegetation, construction, etc. between the mobile in region C and base station 11f, the inclusion of and possible connection to cell VI would not be the optimal choice. A better choice would be cell VII. However, the current cell-centric assignments of neighbor lists would include cell VI. If cell VI were to become the serving cell, the call would be dropped due to the interfering obstacle even though the mobile could be going through cell VI.
Given that there is a limit to the number of neighbors that a mobile station can measure, if a desirable neighbor is not on the list the call can have poor reception or the call could even be dropped. Even if the call is not dropped, the mere size of the list requires the mobile to scan all of the neighbors in that list. As a result, updates to the list are quite slow due to the time it takes to go through the list, and what was initially a good cell candidate has now become a poor cell candidate. However, the mobile still considers it to be a good cell candidate because it has not been able to re-scan that cell. A connection to the cell based upon the initial scan thus results in poor signal quality or even a dropped call. With the increasing pressure to minimize call drops in cellular systems and to improve drop call performance, it is critical that mobile stations operate with the optimal control parameters to avoid dropping calls.
Methods are known to hand over on the basis of a location estimate, while other methods that are known just explain how to locate a mobile station. The problem is that current location technologies do not practically provide absolute location. Consequently, a handover on the basis of a location estimate tends to be closer to a “blind” handover to a neighbor that may not be optimal due to the location inaccuracy as well as a varying radio environment. There are also many methods that are known to find the optimal neighbor list, but they all tie the neighbor list to a specific cell (i.e. they are cell-centric). This results in the problems stated above. Moreover, the above-stated problems extend beyond neighbor lists to other system control parameters that are associated with the serving cell, such as power control, handover thresholds and handover timers.
Thus there is a need for a method and apparatus for generating and assigning an optimal neighbor list or other system control parameters based on the actual location of the mobile station as opposed to a cell-centric system.